11 papers
Unified Video Dense Prediction from Disjoint Data
Yihong Sun, Seoung Wug Oh, Jiahui Huang +2
Scene understanding requires simultaneous prediction about geometry, appearance, and semantics. However, existing task-specific annotations are fragmented across incompatible, doma…
DAGE: Dual-Stream Architecture for Efficient and Fine-Grained Geometry Estimation
Tuan Duc Ngo, Jiahui Huang, Seoung Wug Oh +4
Estimating accurate, view-consistent geometry and camera poses from uncalibrated multi-view/video inputs remains challenging - especially at high spatial resolutions and over long…
VideoMaMa: Mask-Guided Video Matting via Generative Prior
Sangbeom Lim, Seoung Wug Oh, Jiahui Huang +3
Generalizing video matting models to real-world videos remains a significant challenge due to the scarcity of labeled data. To address this, we present Video Mask-to-Matte Model (V…
FRAME: Pre-Training Video Feature Representations via Anticipation and Memory
Sethuraman TV, Savya Khosla, Vignesh Srinivasakumar +5
Dense video prediction tasks, such as object tracking and semantic segmentation, require video encoders that generate temporally consistent, spatially dense features for every fram…
Tuning-Free Multi-Event Long Video Generation via Synchronized Coupled Sampling
Subin Kim, Seoung Wug Oh, Jui-Hsien Wang +2
While recent advancements in text-to-video diffusion models enable high-quality short video generation from a single prompt, generating real-world long videos in a single pass rema…
Elevating Flow-Guided Video Inpainting with Reference Generation
Suhwan Cho, Seoung Wug Oh, Sangyoun Lee +1
Video inpainting (VI) is a challenging task that requires effective propagation of observable content across frames while simultaneously generating new content not present in the o…